The Requirement for a Spectroscopy Management and Laboratory Information Management System

The data and knowledge generated as a result of Chemistry and Pharmaceutical R & D efforts today can commonly be defined as laboratory notebook content, internal technical reports, published literature, a molecular structure database in many cases, and filing cabinets full of analytical data including numeric results, graphs, images and spectra. Despite efforts for computerizing this information these efforts have not given rise to the expected breakthroughs in a lot of areas. In particular, there is a distinct need for a spectroscopic database management system. below the approaches that are available today to aid in the implementation of such a system. The main product of an analytical laboratory is information. Some of this information is in the form of new analytical techniques or methods that extend a laboratory's ability to analyze new materials. For most labs, however, the largest amount of information is in the form of measurements and reports. These measurements are the key to understanding and controlling manufacturing processes, solving manufacturing and development problems, and developing new high-performance materials. Preparing samples, making measurements, analyzing data, and generating reports is the common process analytical laboratories use to generate information. Properly managing this process and tracking the flow of work through the laboratory is critical to the efficient operation of a lab.

Any analytical spectroscopy laboratory can generate in a single year thousands of spectra which are associated with individual samples. In many cases the intention is to utilize these spectra to aid in structural identification and elucidation and therefore the information generated also includes molecular structure information. As a result of the analytical process spectra can fall into three general categories at the completion of analytical measurement on a sample. These three categories can be defined as reference spectra which are deemed to be appropriate descriptors of well-defined molecular structures or materials, consistent spectra which offer spectral features which are consistent with the material, and spectral data which are representative of the sample but offer no conclusive information regarding the identification of the material.

As part of this process the development of appropriate software tools has been an essential component of these efforts. The result has been the initiation of collaborative electronic notebook efforts, the installation of molecular structure databasing tools including those of Molecular Design Limited and Oxford Molecular Group, home grown software applications for laboratory information management, force-fitting of commercial LIMS systems originally developed for the manufacturing environment and the establishing of documented processes and procedures for the tracking of information. The stringent requirements of approving bodies for patenting and drug approval, for example, demand that appropriate trails are in place for the tracking of data and information through the research process to scale-up and then manufacturing.

Figure 1: MDL/ISIS Base showing Spectral Management Toolset (Click on image to enlarge)

Molecular structure databasing tools have been provided by vendors including Molecular Design Limited, Daylight Systems and Oxford Molecular Group. Spectral management systems which are linked to chemical structures have generally been developed in house though recently commercial applications have started to become available which either integrate to the commercial structure database applications (Figure 1 right) or are available as self-contained software components (for example SpecManager available from Advanced Chemistry Development, Figure 2 below). Commercial LIMS systems have rarely delivered to the research environment the appropriate tools to allow the simultaneous management of samples, structure and spectra and approaches have generally adapted commercial components and produced in-house integration schemes or home-built systems have been developed at a number of sites.

Figure 2: SpecManager Spectral, Structure and Sample Detail PC-Based Management (Click on image to enlarge)

When computers became available, analytical laboratories began to use them to help automate many of their processes, including the information handling and generating processes. Analytical chemists and information specialists working to improve their own operations were the first to develop laboratory information management systems, or LIMS. They typically supported only one technique or small unit of a laboratory and did not communicate with other information systems.

The first commercial LIMS arrived on the market in about 1980. Today, there are dozens of LIMS vendors providing packages with many capabilities. There is even a World Wide Web site devoted to providing information on LIMS resources, analyses of the latest technology, and the products and services available from vendors and consultants. In 1993, the American Society for Testing and Materials published a standard guide on LIMS. The guide is intended for anyone interested in LIMS, including users, developers, implementers, and laboratory managers. It defines standard terminology, a concept model, primary functions, an implementation guide, and a checklist. These are useful for discussing and understanding LIMS as well as developing specifications and cost justification. The guide is a good reflection of what was thought a traditional LIMS should be and of what most vendors have marketed.

Many factors drive analytical labs to implement LIMS. These include the need to demonstrate value, comply with detailed regulatory requirements, manage large amounts of samples and tests from automated analysis and screening systems, automate their processes, improve accuracy, and deal with increased demands for efficiency and documentation. Implementing a LIMS can be expensive and have significant impact on laboratory workflow and productivity. For successful implementation of a LIMS, it is important to know which factors are most important and where productivity will be impacted, both positively and negatively. It is also extremely important that the workflow is supported by the LIMS in an appropriate and simple manner.

In the past two years the world has experienced a powerful shift in computing with the explosive growth of the World Wide Web (WWW). With this paradigm shift in capability and function has come a new level of comfort for bench top chemists, researchers and analysts to enter into corporate wide Laboratory Information Management. The Web has provided to the world an intuitive and graphical point-and-click environment for users to travel through a world of complex information and at present the major direction for enhancing corporate communications is via an intranet. There have been similar attempts to address the needs for integrated sample, structure and spectral management including the efforts of Eastman Kodak Company with their Web-based Information Management System, WIMS and the Advanced Chemistry Development Spectral Laboratory Information management System, SLIMS.

The Web-based Information Management System1, WIMS, at Eastman Kodak was initiated by the needs for a LIMS system within the heterogeneous computing environment of the Molecular Spectroscopy Unit. The result is an integrated web-based system that provides access to sample information including reports, structures and spectra. Originally developed to address the needs of the Nuclear Magnetic Resonance group, WIMS consists entirely of HTML, PERL, and ANSI C programs, along with binary databases storing the information. The sample tracking functionality has been integrated with the in-house application Quantum for structure management needs. Spectra can be displayed using a spectral display tool which generates a GIF display from the data. The system has been expanded to include multiple binary flat file databases, one for each analytical area (such as NMR, IR, and MS) since in general most users will generally want to search only the data from their own analytical area. For example, by having NMR data in its own database, searching can proceed much faster than if all data is contained within a single database. Structures and spectra are stored in separate databases and are retrieved and displayed using code written for these tasks.

The information handling requirements of analytical laboratories vary from the research to manufacturing environments. A standard testing laboratory that supports manufacturing quality control and regulatory compliance uses analysis procedures that are well defined and strictly followed. These laboratories analyze relatively large numbers of samples and produce numerical or tabular results that are often plotted against time. Spectral analysis is usually used in the seeenvironments to determine concentration or verify identification relative to some known reference spectrum or spectra.

In contrast, a research analytical laboratory supporting the discovery of new materials uses analysis procedures that are defined in the mind of the analyst. While the analyst may use analytical techniques that are well defined, the process he chooses to apply to a particular sample is not predetermined, but is developed in response to the questions that need to be answered. These laboratories analyze fewer numbers of samples and regularly produce results that combine graphics and images with textual reports. In this environment, spectroscopy is also used to elucidate chemical structure and determine three-dimensional spatial relationships.

Other types of analytical laboratory environments vary between these two idealized ones. Process control environments model a fully automated standard testing laboratory. High throughput screening is similar, but often includes special processing for unusual results or potentially interesting materials. Like research, problem solving does not follow a fixed analytical process, but often results must be expressed in manufacturing terms. Development environments reflect the need to move research testing for understanding to standard testing for manufacturing. Problems arise when a LIMS vendor tries to sell one generalized solution, customized to fit all environments.

Figure 3: Web-based Java Tools for Spectral Display (Click on image to enlarge)

The SLIMS system2 developed by Advanced Chemistry Development is a highly extended modification of the basic WIMS concept. SLIMS offers access to a tool kit that includes sample management and tracking, sample hierarchies including new sample, pool sample, active sample and abandoned sample, sample statistics and analysis, a structure management database module incorporating platform independent Java applet technology for structure drawing, a spectral management database module for management of NMR, MS, IR, UV-Vis, Raman, LC and other spectral curve technologies utilizing Java applets for spectral display (Figure 3 left) and manipulation and integration with desktop products for spreadsheets, reports of analysis and chemical structures and spectra.

The spectral database module allows management of spectral data including spectral display and manipulation on the web, sample and literature spectral database construction, spectral and subspectral searching and management of standard spectral formats (JCAMP, SPC, NetCDF, ASCII). Flexible spectral search capabilities based on text fields and spectral matching as well as full subspectral search capabilities are available. Spectra can also be downloaded directly to PC-based desktop applications. Since SLIMS is a web-based integration of sample, structure and spectral management utilizing Java-based structure drawing and spectral display applets the Java implementation and compatability with Netscape and Microsoft browsers ensures a platform independence for the system.

The need to manage sample, structure and spectral information in a single environment is obvious and has been revisited in this article. A number of approaches ranging from desktop-based spectral management systems with structural associations as well as web-based LIMS systems with structure and spectral ties are now available.